Measurement methods for perceptually adapted quality assessment of audio signals are generally known. The basic structure of a measurement method of this type includes mapping the input signals onto an perceptually adapted time-frequency representation, comparing this representation, and calculating individual numeric values in order to estimate the discernible disturbances. Reference is made in this regard to the following publications:    Schroeder, M. R.; Atal, B. S.; Hall, J. L: Optimizing Digital Speech Coders by Exploiting Masking Properties of the Human Ear. J. Acoust. Soc. Am., Vol. 66 (1979), No. 6, December, pages 1647–1652;    Beerends, J. G.; Stemerdink, J. A.: A Perceptual Audio Quality Measure Based on a Psychoacoustic Sound Representation. J. AES, Vol. 40 (1992), No. 12, December, pages 963–978; and    Brandenburg, K. H.; Sporer, Th.: NMR and Masking Flag: Evaluation of Quality Using Perceptual Criteria. Proceedings of the AES 11th International Conference, Portland, Oreg., USA, 1992, pages 169–179, all three of which are hereby incorporated by reference herein.
As described in these publications, however, the models used for assessing coded audio signals employ FFT (fast Fourier transform) algorithms and thus require the linear frequency division predetermined by the FFT to be converted to an perceptually adapted frequency division. This makes the time resolution less than optimal. In addition, convolution with a spreading function is carried out after rectification or absolute-value generation, reducing the spectral resolution without increasing the temporal resolution correspondingly.
Additionally, fast filter bank algorithms which, for example, can be used for calculating short time Fourier transforms in, for example, very large scale integrated (VLSI) circuits, are known. See Liu, K. J. R.: Novel Parallel Architectures for Short-Time Fourier Transform. IEEE Trans. on Cir. and Sys.-II: Anal. and Dig. Sig. Proc., Vol. 40, No. 12, December 1993, pages 786–790.